Journal of Computer Applications ›› 2011, Vol. 31 ›› Issue (05): 1344-1347.DOI: 10.3724/SP.J.1087.2011.01344

• Database technology • Previous Articles     Next Articles

Improved measure of similarity between intuitionistic fuzzy rough sets

FAN Cheng-li, LEI Ying-jie, ZHANG Ge   

  1. Missile Institute, Air Force Engineering University, Sanyuan Shaanxi 713800, China
  • Received:2010-11-04 Revised:2011-01-01 Online:2011-05-01 Published:2011-05-01

改进的直觉模糊粗糙集相似性度量方法

范成礼,雷英杰,张戈   

  1. 空军工程大学 导弹学院, 陕西 三原 713800
  • 通讯作者: 范成礼
  • 作者简介:范成礼(1988-),女,四川眉山人,硕士研究生,主要研究方向:智能信息处理、信息融合;雷英杰(1956-),男,陕西渭南人,教授,博士生导师,博士,主要研究方向:智能信息处理、智能决策;张戈(1986-),男,山西运城人,硕士研究生,主要研究方向:智能信息处理、信息融合。
  • 基金资助:

    国家自然科学基金资助项目(60773209)。

Abstract: An improved measure of similarity based on the Hamming distance for measuring the degree of similarity between intuitionistic fuzzy rough sets was proposed on the basis of analyzing the deficiency of the existing similarity measure method. This method solved the problem of inaccurate similarity measure by adding the hesitancy degree and weight. Firstly, a similarity measure method for the degree of similarity between two intuitionistic fuzzy rough elements was given, and several important characters of it were revealed. Furthermore, a similarity measure method based on the Hamming distance for the degree of similarity between intuitionistic fuzzy rough sets was presented. This method was proved to have the same characters. At last, this improved similarity measure method is confirmed to be more reasonable and effective by examples.

Key words: similarity measure, intuitionistic fuzzy rough set, intuitionistic fuzzy rough element, Hamming distance

摘要: 针对现有的直觉模糊粗糙集相似性度量的问题,提出了一种改进的基于海明距离的直觉模糊粗糙集相似性度量方法。该方法考虑了犹豫度并引入加权参数,解决了相似性度量不精确的问题。首先给出了直觉模糊粗糙值间的相似性度量定义,并揭示其若干重要性质。在此基础上,提出了直觉模糊粗糙集间的相似性度量方法,并证明其具有同样性质。最后通过数值算例分析说明了该方法更合理、更有效。

关键词: 相似性度量, 直觉模糊粗糙集, 直觉模糊粗糙值, 海明距离